1. Field of the Invention
The present invention relates to an appearance inspection machine and method for semiconductor wafers. More particularly, this invention is concerned with a technology for quickly inspecting the appearance of a semiconductor wafer as a whole.
2. Description of the Related Art
In general, a semiconductor wafer manufacturing process consists of about 300 to 500 steps. If a defect occurred at each step, an enormous number of defects would be found at the last step. This is because a defect occurring at one step is accumulated on defects having occurred previously. For improving the yield of a product, ideally, the appearance of the product is inspected at each step. However, this is unfeasible in terms of cost and labor. In reality, the appearance of the product is inspected at some steps. For further improving the manufacturing efficiency, appearance inspection should preferably be included in the manufacturing process. There is therefore a demand for high-precision appearance inspection that can be performed as quickly as the manufacturing process progresses.
In general, appearance inspection falls into defect detection and automatic defect classification (ADC). The defect detection is performed on a whole semiconductor wafer by an image processing unit. The automatic defect classification is performed by an automatic defect classification (ADC) system for automatically classifying a defect detected through the defect detection into a category. According to a prior art, after defect detection performed on a whole semiconductor wafer is completed, a stage is moved in order to pick up the image of a defective area. Image data of the defective area is then stored in the ADC system. Image data of a normal counterpart of an adjacent die is stored in the ADC system.
In a conventional appearance inspection machine, after defect detection is completed, a stage is moved in order to acquire image data of an analysis-needed part and normal part. The image data is processed for classifying a defect. The time required for processing is therefore equal to a sum of the time required for defect detection accompanied by scanning and the time required for acquisition and classification of analysis image data accompanied by movement of the stage.
As far as the conventional appearance inspection machine is concerned, the processing time is equal to the sum of the time required for detect detection and the time required for acquisition and classification of analysis image data. The processing time is therefore very long. The time that can be spent for inspecting the appearance of one semiconductor wafer is limited and must be further shortened.
For example, an image projected at a high magnification may be sampled by a TDI sensor. In this case, it takes 30 min to one hour to detect a defect on one semiconductor wafer. It is therefore required to acquire and classify analysis image data in 10 mins, or less. To reduce the processing time, the number of analysis-needed parts is decreased. This brings about the current situation that analysis cannot be carried out satisfactorily.
The present invention attempts to solve the foregoing problems. An object of the present invention is to provide an appearance inspection machine and method capable of classifying a defect automatically and efficiently and analyzing a defect for a short time. Specifically, the present invention is intended to shorten the processing time required for an entire appearance inspection and to improve the throughput of inspection.
To accomplish the object, in an appearance inspection machine and method in accordance with the present invention, an analysis buffer is included for temporarily storing acquired image data. As soon as defect information is produced according to the results of comparison, an analysis-needed defect is selected. Image data required for analyzing the analysis-needed part is transferred from the analysis buffer to an automatic defect classification unit. Thus, defect detection and classification are partly carried out concurrently.
An appearance inspection machine according to the present invention comprises an image acquisition unit, a defect information production unit, and an automatic defect classification unit. The image acquisition unit sequentially acquires image data of each die by scanning a semiconductor wafer having dice formed thereon. The defect information production unit compares acquired image data with image data of a counterpart of another die so as to detect a defect, and produces defect information sequentially. The automatic defect classification unit automatically classifies a defect according to the image date of at least part of the detected defect. The defect information production unit consists of a comparison buffer memory, an image comparison unit, an analysis buffer memory, and a sampling and control unit. Acquired image data is temporarily stored in the comparison buffer memory. The image comparison unit compares image data with a counterpart of image data stored in the comparison buffer memory. The sampling and control unit selects an analysis-needed part of which defect is classified automatically using the automatic defect classification unit according to sequentially-produced defect information. The sampling and control unit then transfers image data necessary to analyze the analysis-needed part to the automatic defect classification unit. As soon as defect information is produced, the sampling and control unit selects an analysis-needed part and transfers image data. The automatic defect classification unit sequentially classifies transferred image data. Thus, defect detection by the defect information production unit and classification by the automatic classification unit are partly carried out concurrently.
Moreover, an appearance inspection method in accordance with the present invention comprises an image acquisition step, a defect information production step, and an automatic defect classification step. At the image acquisition step, image data of each die is acquired sequentially by scanning a semiconductor wafer having a plurality of dice formed thereon. At the defect information production step, acquired image data is compared with a counterpart of another die in order to defect a defect, and defect information is produced sequentially. At the automatic defect classification step, a defect is classified automatically by checking the image data of at least part of the detected defect. The defect information production step comprises a comparison data storage step, an image comparison step, an analysis data storage step, an automatic defect classification step, and a sampling and control step. At the comparison data storage step, acquired image data is temporarily stored as comparison image data. At the image comparison step, image data is compared with a counterpart of the comparison image data in order to detect a defect. At the analysis data storage step, acquired image data is temporarily stored as analysis image data. At the sampling and control step, an analysis-needed part whose defect is automatically classified at the automatic defect classification step is selected based on the sequentially produced detect information. Image data necessary to analyze the analysis-needed part is transferred to an automatic defect classification memory. At the sampling and control step, as soon as detect information is produced, selection of an analysis-needed part and transfer of image data are carried out immediately. At the automatic defect classification step, a defect is classified based on transferred image data. Thus, defect detection at the defect information production step and classification at the automatic defect classification step are partly carried out concurrently.
According to the appearance inspection machine and method of the present invention, the analysis buffer memory is included for temporarily storing image data. It is judged whether the stored image data is necessary to analyze an analysis-needed part. If it is judged that the stored image data is necessary, the image data is preserved until it is transferred to a memory in the automatic defect classification memory. If it is judged that the stored image data is unnecessary, or that transfer is completed, the image data is released and the next image data is stored. The storage capacity of the analysis buffer memory may therefore be relatively small. According to these constituent features, defect detection and automatic defect classification are partly carried out concurrently. The time required for entire inspection will not be extended but the time required for automatic detect classification can be extended. This leads to satisfactory analysis. Moreover, it is unnecessary to acquire image of the analysis-needed part again. The inspection time can therefore be shortened accordingly. For example, according to the prior art, it takes 30 min to detect a defect, and it takes 10 min to acquire the image of an analysis-needed part and automatically classify the defect. In this case, the inspection time comes to 40 min. According to the present invention, automatic defect classification alone can be carried out over about 40 min that is the same as the above inspection time. Eventually, analysis can be achieved in more detail.
For detailed analysis, a level to be set for comparison in the image comparison unit is lowered in order to detect a larger number of defects. However, since selection of an analysis-needed part is carried out concurrently, analysis information that has been checked for selection is sequentially deleted. The storage capacity of a defect list memory need not be increased.
Conventionally, since the time required for automatically defect classification is insufficient, a significant defect is mainly analyzed. Image comparison is achieved by judging whether a difference between two image data items is larger than a set value. However, according to the present invention, automatic defect classification can be achieved accountely. During image comparison, information concerning the location and size of a defective part, the gray-scale level thereof, and a difference in gray-scale level thereof from a compared part can be output as defect information. An amount of image data to be checked for selecting an analysis-needed part, that is, for automatically classifying a defect is adjusted dynamically according to an amount of image data that can be checked for automatically classifying a defect within a certain time. For example, the occurrence frequency of a defect is low for some time since the start of inspection. The occurrence frequency may rise in the course of inspection. In this case, the criterion of selecting an analysis-needed part is lowered so that even a small defect will be selected as an analysis-needed part. In the course of inspection, the criterion of selection is raised so that the small defect will not be selected as an analysis-needed part. Consequently, an ADC system can be operated efficiently.
Image data to be transferred from an analysis buffer memory to an automatic defect classification unit includes image data of an image area covering an analysis-needed part, and its surroundings, which is required for automatic defect classification, and image data of a counterpart of an adjacent normal die. The size of the image area represented by image data to be transferred is varied depending on the size of the analysis-needed defect. Image data to be transferred is part of image data stored in the analysis buffer memory. The amount of image data is very small for that of the whole image data.
The storage capacity of the analysis buffer memory depends on the processing time required until an analysis-needed part is selected, and must be large enough to store image data acquired by scanning a row having the largest number of dice. In this case, the analysis buffer memory can be controlled easily.
Furthermore, image data read from at least part of the analysis buffer memory should be able to be supplied to the image comparison unit. This enables double detection to be performed on an edge die in the course of inspection.
Furthermore, image data read from the analysis buffer memory should be able to be supplied to the image comparison unit. In this case, the analysis buffer memory can be used as a comparison buffer. Another comparison buffer can be excluded.
The analysis buffer memory has a plurality of banks in each of which image data acquired by scanning one die once can be stored. The analysis buffer memory is structured so that data can be written in or read from the banks concurrently.
According to the prior art, the comparison buffer memory is included for temporarily storing image data. In the comparison buffer memory, when image data of the next die is acquired for comparison with stored image data, the image data of the next die is stored at the same time. When an analysis-needed part is detected, the image data has already been lost and cannot therefore be transferred to the automatic defect classification unit for use.